def jensenfilter(funddf, indexdf, rf, ratio):
funddfr = funddf.pct_change().fillna(0.0)
indexdfr = indexdf.pct_change().fillna(0.0)
jensen = {}
cols = funddfr.columns
for col in cols:
p = []
m = []
rs = funddfr[col].values
#print col, rs
indexrs = indexdfr.values
for i in range(0, len(rs)):
if isnan(rs[i]):
continue
else:
p.append(rs[i])
m.append(indexrs[i])
jensen[col] = fin.jensen(p, m, rf)
x = jensen
sorted_x = sorted(x.iteritems(), key=lambda x : x[1], reverse=True)
sorted_jensen = sorted_x
result = []
for i in range(0, (int)(len(sorted_jensen) * ratio)):
result.append(sorted_jensen[i])
return result
def fund_jensen(funddf, indexdf):
rf = 0.03 / 52
funddfr = funddf.pct_change().fillna(0.0)
indexdfr = indexdf.pct_change().fillna(0.0)
jensen = {}
cols = funddfr.columns
for col in cols:
p = []
m = []
rs = funddfr[col].values
#print col, rs
indexrs = indexdfr.values
for i in range(0, len(rs)):
if isnan(rs[i]):
continue
else:
p.append(rs[i])
m.append(indexrs[i])
jensen[col] = fin.jensen(p, m, rf)
x = jensen
sorted_x = sorted(x.iteritems(), key=lambda x: x[1], reverse=True)
sorted_measure = sorted_x
return sorted_measure
def pool_by_corr_jensen(pool, day, lookback, limit):
index = base_trade_dates.trade_date_lookback_index(end_date=day, lookback=lookback)
start_date = index.min().strftime("%Y-%m-%d")
end_date = day.strftime("%Y-%m-%d")
ra_index_id = pool['ra_index_id']
pool_id = pool['id']
df_nav_index = base_ra_index_nav.index_value(start_date, end_date, ra_index_id)
#df_nav_index.index.name = str(df_nav_index.index.name)
df_nav_index.columns = df_nav_index.columns.astype(str)
if len(df_nav_index.index) == 0:
return []
pool_codes = asset_ra_pool_sample.load(pool_id)['ra_fund_code'].values
df_nav_fund = base_ra_fund_nav.load_daily(start_date, end_date, codes = pool_codes)
if len(df_nav_fund) == 0:
return []
df_nav_fund = df_nav_fund.reindex(pd.date_range(df_nav_index.index[0], df_nav_index.index[-1]))
df_nav_fund = df_nav_fund.fillna(method = 'pad')
df_nav_fund = df_nav_fund.dropna(axis = 1)
df_nav_fund = df_nav_fund.loc[df_nav_index.index]
fund_index_df = pd.concat([df_nav_index, df_nav_fund], axis = 1, join_axes = [df_nav_index.index])
fund_index_corr_df = fund_index_df.pct_change().fillna(0.0).corr().fillna(0.0)
corr = fund_index_corr_df[ra_index_id][1:]
corr = corr.sort_values(ascending = False)
code_jensen = {}
for code in df_nav_fund.columns:
jensen = fin.jensen(df_nav_fund[code].pct_change().fillna(0.0), df_nav_index[ra_index_id].pct_change().fillna(0.0) ,Const.rf)
code_jensen.setdefault(code, jensen)
if len(code_jensen) == 0:
logger.info('No FUND')
return None
else:
final_codes = []
x = code_jensen
sorted_x = sorted(iter(x.items()), key=lambda x : x[1], reverse=True)
corr_threshold = np.percentile(corr.values, 80)
corr_threshold = 0.7 if corr_threshold <= 0.7 else corr_threshold
corr_threshold = 0.9 if corr_threshold >= 0.9 else corr_threshold
for i in range(0, len(sorted_x)):
code, jensen = sorted_x[i]
if corr[code] >= corr_threshold:
final_codes.append(code)
final_codes = final_codes[0 : limit]
return final_codes
def jensenmeasure(funddf, indexdf, rf):
funddfr = funddf.pct_change().fillna(0.0)
indexdfr = indexdf.pct_change().fillna(0.0)
jensen = {}
cols = funddfr.columns
for col in cols:
p = []
m = []
rs = funddfr[col].values
#print col, rs
indexrs = indexdfr.values
for i in range(0, len(rs)):
if isnan(rs[i]):
continue
else:
p.append(rs[i])
m.append(indexrs[i])
jensen[col] = fin.jensen(p, m, rf)
return jensen
indexrs = []
for i in range(1, len(indexvs)):
indexrs.append(indexvs[i] / indexvs[i-1] - 1)
rf = 0.025 / 52
jensen = {}
sortino = {}
for code in fundrs.keys():
rs = fundrs[code]
if len(rs) < len(indexrs):
continue
jensen[code] = fin.jensen(rs, indexrs, rf)
sortino[code] = fin.sortino(rs, rf)
#print jensen[codes[i]]
#print sortino[codes[i]]
#print jensen
#print sortino
#print dates
x = jensen
sorted_x = sorted(x.iteritems(), key=lambda x : x[1], reverse=True)
sorted_jensen = sorted_x
x = sortino